Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Graphical models are well established in providing compact conditional probability descriptions of complex multivariable interactions. In the Gaussian case, graphical models are d...
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee
Rank correlation measures are known for their resilience to perturbations in numeric values and are widely used in many evaluation metrics. Such ordinal measures have rarely been ...
Jay Yagnik, Dennis Strelow, David Ross, Ruei-sung ...
Microarray experiments are emerging as one of the main driving forces in modern biology. By allowing the simultaneous monitoring of the expression of the entire genome for a given...